Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study

This study aimed to develop an early pregnancy risk scoring model for pregnancy-associated hypertension (PAH) based on maternal pre-pregnancy characteristics, such as mean arterial pressure (MAP), pregnancy-associated plasma protein-A (PAPP-A) or neither. The perinatal databases of seven hospitals from January 2009 to December 2020 were randomly divided into a training set and a test set at a ratio of 70:30. The data of a total pregnant restricted population (women not taking aspirin during pregnancy) were analyzed separately. Three models (model 1, pre-pregnancy factors only; model 2, adding MAP; model 3, adding MAP and PAPP-A) and the American College of Obstetricians and Gynecologists (ACOG) risk factors model were compared. A total of 2840 (8.11%) and 1550 (3.3%) women subsequently developed PAH and preterm PAH, respectively. Performances of models 2 and 3 with areas under the curve (AUC) over 0.82 in both total population and restricted population were superior to those of model 1 (with AUCs of 0.75 and 0.748, respectively) and the ACOG risk model (with AUCs of 0.66 and 0.66) for predicting PAH and preterm PAH. The final scoring system with model 2 for predicting PAH and preterm PAH showed moderate to good performance (AUCs of 0.78 and 0.79, respectively) in the test set. “A risk scoring model for PAH and preterm PAH with pre-pregnancy factors and MAP showed moderate to high performances. Further prospective studies for validating this scoring model with biomarkers and uterine artery Doppler or without them might be required”.

Life 2023, 13, 1330 3 of 19 or multiorgan involvement, which may manifest as thrombocytopenia, renal dysfunction, hepatocellular necrosis, central nervous system perturbations, or pulmonary edema [15]. The criteria of PE were hypertension plus proteinuria or multiorgan involvement reflected by thrombocytopenia, renal dysfunction, hepatocellular necrosis, central nervous system perturbations, or pulmonary edema [15]. Superimposed PE is diagnosed in women who have PE superimposed on chronic hypertension. Eclampsia is diagnosed in women with PE and new-onset seizures in the absence of other causative conditions [15]. Unspecified maternal hypertension refers to the diagnosis of hypertension in women within 40 weeks before or 12 weeks after delivery who do not meet the criteria for either chronic or pregnancy-induced hypertension [16].
To confirm the diagnosis and fill in missing data, a chart review was done by two maternal fetal medicine doctors (H.S.K. and J.H.W.). Preterm PAH was defined as cases who had a delivery before 37 weeks of gestation due to PAH. Baseline and clinical characteristics of the group affected by PAH and the group without PAH (control) were compared. Prepregnant maternal body mass index (BMI, kg/m 2 ) before pregnancy was calculated from measured height, and weight (at delivery), and self-reported prepregnant body weight. Maternal blood pressure was measured on the right upper arm using manual blood pressure equipment with a cuff size appropriate for arm circumference. Korotkoff V was used for diastolic blood pressure.
The history of previous pregnancy complications, including PE, fetal death in utero (FDIU), fetal growth restriction (FGR), gestational diabetes (GDM), and preterm birth before 37 weeks of gestation, was obtained from the obstetric record. The diagnosis of GDM in the current pregnancy was based on the ICD code assigned during pregnancy (ICD10 codes O24.4 or O24.9), excluding women with a pre-pregnancy record of diabetes (defined as any of the ICD10 codes O24.0-24.3 or E12- 14) or prescription codes for insulin or other diabetes medication. GDM screening test results were also considered using a two-step procedure routinely performed for all women at 24-28 weeks of pregnancy, following NIH guidelines [17,18]. The first recorded blood pressure before 20 weeks of gestation was collected for women with available data. MAP, calculated as (systolic blood pressure + (2 × diastolic blood pressure))/3, was used in prediction models (models 2 and 3). Additionally, multiples of the median (MoM) values of PAPP-A in maternal serum screening tests during the first trimester were extracted for women with available data and used in model 3. Maternal serum PAPP-A was measured between 11 + 0 and 13 + 6 weeks of pregnancy as part of a routine aneuploidy screening. To account for the variations in serum marker concentrations according to gestational age, MoM values of PAPP-A for the corresponding gestational age were retrieved from the screening records for women with available data.

Restricted Population
To avoid the influence of aspirin during pregnancy, another analysis for the restricted population after excluding women who took aspirin during pregnancy based on the medical records was performed.

Datasets of Original and Restricted Populations
The original dataset was randomly divided into two sub-cohorts (a model development cohort or training set) and a validation cohort or test set) at a ratio of 70:30. The data set of the restricted population was also divided into training and test sets at a ratio of 70:30.

Statistics
All the analyses were performed using SAS software, version 9.4 (SAS Institute, Inc., Cary, NC, USA). A chi-squared test and a two-sample t-test were used for comparing the variables of the study population for women who did or did not develop PAH. Bivariate associations of PAH and each predictor variable were evaluated with a chi-square test for categorical variables and a t-test for continuous variables. Variables with a statistical Life 2023, 13, 1330 4 of 19 difference in the univariate analysis were included in the multivariable stepwise logistic regression models. After comparing the performances of the three different multivariable regression models (model 1, clinical factor only; model 2, clinical factor and MAP; and model 3, clinical factor, MAP, and PAPP-A) based on the values of the area under the curve (AUC) and the sensitivity of PAH at 10% false positive rate (FPR), a statistic scoring model was developed to stratify the risks for PAH. The performance of the ACOG risk classification guideline for the prevention of PE was also evaluated. Diagnostic accuracy of the scoring system was performed with receiver operating characteristic (ROC) curves. Statistical significance was defined as a two-sided p-value < 0.05.

Baseline Characteristics
In a total of 35,098 cases of delivery, 35,004 cases were included, excluding 94 cases with an age less than 18 years. There were a total of 2840 pregnant women with PAH (1988 women in the training set and 852 women in the validation set), with an incidence rate of 8.11%. There were a total of 1550 pregnant women with preterm PAH (1085 women in the training set and 465 women in the validation set), with an incidence rate of 3.30% ( Figure 1). A flow chart for the restricted population after excluding 666 women who took aspirin during pregnancy is presented in Figure A1.
associations of PAH and each predictor variable were evaluated with a chi-square test categorical variables and a t-test for continuous variables. Variables with a statistical d ference in the univariate analysis were included in the multivariable stepwise logistic gression models. After comparing the performances of the three different multivaria regression models (model 1, clinical factor only; model 2, clinical factor and MAP; a model 3, clinical factor, MAP, and PAPP-A) based on the values of the area under t curve (AUC) and the sensitivity of PAH at 10% false positive rate (FPR), a statistic scori model was developed to stratify the risks for PAH. The performance of the ACOG r classification guideline for the prevention of PE was also evaluated. Diagnostic accura of the scoring system was performed with receiver operating characteristic (ROC) curv Statistical significance was defined as a two-sided p-value < 0.05.

Baseline Characteristics
In a total of 35,098 cases of delivery, 35,004 cases were included, excluding 94 cas with an age less than 18 years. There were a total of 2840 pregnant women with PAH (19 women in the training set and 852 women in the validation set), with an incidence rate 8.11%. There were a total of 1550 pregnant women with preterm PAH (1085 women in t training set and 465 women in the validation set), with an incidence rate of 3.30% (Figu 1). A flow chart for the restricted population after excluding 666 women who took aspi during pregnancy is presented in Figure A1. Baseline and clinical characteristics of the subjects in the training set for analysi and analysis 2 are presented in Table 1. The mean maternal age, BMI before pregnan proportions of nulliparity, pregnancies by in vitro fertilization, multiple pregnan  Baseline and clinical characteristics of the subjects in the training set for analysis 1 and analysis 2 are presented in Table 1. The mean maternal age, BMI before pregnancy, proportions of nulliparity, pregnancies by in vitro fertilization, multiple pregnancy, family history of hypertension, history of hypertension, renal disease, hyperlipidemia, diabetes, insulin glucose tolerance (IGT), lupus or anti-phospholipid syndrome (APS), other rheumatic diseases, and aplastic anemia were significantly higher in the PAH group and the preterm PAH group than in the control group. Pregnancies with a smoking and drinking history and a history of IGT were significantly higher in the PAH group, but not significantly higher in the preterm PAH group, compared to the control group. In multiparous women, histories of PE, FDIU, FGR, GDM, and preterm birth in a previous pregnancy were significantly higher in both PAH and preterm PAH groups than in the control group. The MAPs before 20 weeks of gestation were available for 4822 women. There were significant differences in the MAP between the PAH and control groups (95.4 ± 14.44 mmHg vs. 83.36 ± 9.73 mmHg, p < 0.001) and between the preterm PAH and control groups (100.21 ± 17.44 mmHg vs. 83.36 ± 9.73 mmHg, p < 0.0001). MoM values of PAPP-A between 11 weeks and 13 weeks of gestation were available for 4748 women. There were significant differences in the MoM value between the PAH and control groups (1.04 ± 0.69 MoM vs. 1.19 ± 0.66 MoM, p < 0.0001) and between the preterm PAH and control groups (1.04 ± 0.71 MoM vs. 1.19 ± 0.66 MoM, p = 0.0044). The baseline and clinical characteristics of subjects in the training set of the restricted population are presented in Table A1.  Table 2). When another analysis for model 2 was performed for women with MAPs before 20 weeks of gestation, MAP was significantly associated with PAH (OR: 1.066, 95% CI: 1.054-1.079) ( Table 3). When the last analysis for model 3 was performed for women with MAPs before 20 weeks of gestation and PAPP-A values, the MAPs and MoM values of PAPP-A were significantly associated with PAH (OR: 1.055, 95% CI: 1.036-1.075 and OR: 0.473, 95% CI: 0.265-0.844, respectively) (Table A2).

Performance of Scoring Models for Predicting PAH and Preterm PAH in Total and Restricted Populations
AUC values for predicting PAH and preterm PAH in the total and restricted populations without aspirin treatment during pregnancy are given in Table 6. Based on the variables included, AUCs in models 2 and 3 reached over 0.82 in both total and restricted populations, indicating a moderate-to-high predictive ability. Sensitivities at a 10% FPR for predicting PAH and preterm PAH were higher with model 2 (54.8% and 66.4%, respectively) and model 3 (53.8% and 60.3%, respectively) than with model 1 (41.0% and 38.9%, respectively) for the total population. Sensitivities at a FPR of 10% for predicting PAH and preterm PAH were higher with model 2 (52.2% and 65.5%, respectively) and model 3 (50.4% and 58.1%, respectively) than with model 1 (41% and 41.5%, respectively) for the restricted population. When risk factors of the ACOG risk classification guidelines for preventing PE were applied, AUC was 0.67 in the total population and 0.66 in the restricted population. Sensitivities at a FPR of 10% were 31.0% and 29.4% in the total population and the restricted population, respectively.

Development of a Scoring System with Validation
Based on performance results, the scoring systems for PAH and preterm PAH were constructed using model 2 (Figure 2a,b). BMI and MAP were divided into 5 and 6 categories, respectively. Other factors (age, nulliparity, fetal number in this pregnancy, history of hypertension, diabetes, lupus or APS, renal disease, and history of previous preeclampsia) were divided into two categories. The ROC curves of the scoring system with the training set and the test set to predict PAH (AUC = 0.76 in the training set and AUC = 0.78 in the test set) and preterm PAH (AUC = 0.84 in the training set and AUC = 0.79 in the test set) are given in Figure 3. In the restricted population, the ROC curves of the scoring system showed similar results for predicting PAH (AUC = 0.75 in the training set and AUC = 0.74 in the test set) and preterm PAH (AUC = 0.75 in the training set and AUC = 0.71 in the test set).

Discussion
In this study, the incidences of PAH and preterm PAH were 8.11% and 3.30%, respectively, which were similar to the recent prevalence of HDP in Korea (8.0-9.0%) [16]. However, the cases with chronic hypertension only were not included in the outcomes of PAH, as there is no need to predict it unless superimposed PE develops. The incidence of PAH

Discussion
In this study, the incidences of PAH and preterm PAH were 8.11% and 3.30%, respectively, which were similar to the recent prevalence of HDP in Korea (8.0-9.0%) [16]. However, the cases with chronic hypertension only were not included in the outcomes of PAH, as there is no need to predict it unless superimposed PE develops. The incidence of PAH was relatively high compared to the known incidence [1]. This might be attributed to the fact that secondary or tertiary hospitals have a higher proportion of high-risk pregnancies.
This study investigated independent early pregnancy risk factors for PAH and preterm PAH and developed various prediction models for PAH according to basic characteristics of mothers with MAP and PAPP-A or without them. A prediction model with basic maternal characteristics with MAP (model 2) showed the best performance and a scoring system was developed with this model. The performance of model 2 was superior to a model based on ACOG clinical risk assessment for PE [6].
The NICE [7] and ACOG [6] guidelines defined high-risk groups for PE by clinical factors in women with one or more high-risk factors or with two or more moderate risk factors and recommended aspirin prophylaxis for them. Clinical factors included in these two guidelines were different. Studies comparing performances of these two guidelines showed differences in the results by country and race. In a study on Asian subjects, the ACOG guidelines showed better performance than NICE [19]. High risk factors in the ACOG guidelines are history of PE, multifetal gestation, chronic hypertension, diabetes, renal disease, autoimmune disease. Moderate risk factors in the ACOG guidelines are nulliparity, obesity (BMI: 30 kg/m 2 ), African American race, low socioeconomic status, age 35 years or older, and personal history factors (e.g., low birth weight or small for gestational age, previous adverse pregnancy outcome, more than 10-year pregnancy interval). However, maternal age and multiple pregnancies have increased in South Korea. The percentage of women aged 35 years or older was reported to be 35%, with the percentage of nulliparity exceeding 32.3% and multiple pregnancies exceeding 5.4% [20][21][22].
If the Korean society of obstetrics and gynecology follows the ACOG guidelines, it seems that over 30% of pregnant women in Korea require aspirin during pregnancy. The ACOG and U.S. preventive services task force team have suggested a high-risk group for preventive aspirin treatment when the risk of PE is over 8% [6]. In our scoring system, if the score exceeds 13 points, the risk becomes greater than 8%. Only MAP ≥ 97 mmHg before 20 weeks of gestation had a high risk (24 points with risk over 8%) as a single factor. A revised guideline by the American College of Cardiology and American Heart Association in 2017 defined high blood pressure (130-190/80-90 mmHg) as a stage 1 hypertension and suggested pharmacologic treatment in a non-pregnant status [23]. However, the ACOG continues to support a diagnosis of chronic hypertension in pregnancy when blood pressure is confirmed to be ≥140/90 mmHg [15]. There is increasing evidence supporting an association between stage 1 hypertension and the development of PE [24][25][26], as well as the benefits of treatment for mild chronic hypertension during pregnancy to reduce adverse pregnancy outcomes without impairing fetal growth [27]. In 2022, the SMFM recommended treatment with antihypertensive therapy for mild chronic hypertension in pregnancy to a goal BP of <140/90 mmHg based on recent evidence [28]. As an MAP calculated by 130/80 mmHg becomes 97 mmHg, which is correlated with the cut off value of high-risk factor in this study, those with blood pressure of 130-190/80-90 mmHg before 20 weeks of gestation might need close observation.
In this study, other risk factors including maternal age of 40 years or above, nulliparity, and multiple pregnancy showed moderate risks. In a case of a 39-year-old or 34-year-old nulliparous woman with twin gestation and initial MAP of 80 mmHg, if there are no other risk factors, the total score is 10 points, representing a risk of 5.78%. Therefore, they might not belong to the group recommended for taking aspirin. On the other hand, in the case of a 35-year-old nulliparous woman with twin gestation and diabetes, the total score is 15 points, representing a risk of 10.57%, and therefore aspirin use may be recommended. Even in a 41-year-old nulliparous woman with singleton gestation, BMI of 20 kg/m 2 , and MAP of 80 mmHg without any underling diseases, the total score is 9 points, representing a risk of 5.11%, meaning that aspirin prophylaxis is not indicated by this study model, but indicated by the ACOG criteria. Based on this study, it seems that personal health status has more importance. However, if the same woman gets pregnant with twins, the total score becomes 14 points, representing a risk of 9.39%, which may require aspirin during pregnancy. Another considering point is the prevalence of PAH. Among East-Asian women including Chinese, Japanese, and Korean, the prevalence of hypertensive disorders in pregnancy is about 1-5%, which is much lower than those (3.3 to 15.8%) in non-Hispanic Black, African American, and Black women in US and those (0.4 to 10%) in non-Hispanic White women [29,30]. Therefore, the KSOG needs to discuss whether they should define a high-risk group for preventive aspirin treatment when the risk of PAH is over 8% or other lower cut-off values. -

Limitations and strengths of this study
This study has several limitations. Firstly, we could not extract information about family history of PE (mother or sister) or the interpregnancy interval from the EMR because it was not routinely recorded. Secondly, the MoM values of PAPP-A for the relevant gestational age were taken from routine screening records, and because the measurements of PAPP-A did not come from one central lab, there can be some bias. Thirdly, there were missing values, especially in model 3, including PAPP-A, which might have affected its performance. However, as non-invasive prenatal testing (NIPT) with high sensitivity and low false positive rate for the detection of Down syndrome was indicated mainly in high-risk pregnant women including women aged 35 years or more [31], NIPT has been widely used as an initial fetal aneuploidy screening test rather than a maternal serum screening including PAPP-A [32] in those women. Therefore, uterine artery Doppler and biochemical markers of PAPP-A and placental growth factor (PLGF) suggested by the FMF prediction model for gestational hypertension might require another cost for application of the FMF model in high-risk pregnant women [10,33]. A previous study in Asia including the FMF prediction model, FMF triple test by a combination of maternal factors, MAP, uterine artery pulsatility index, and PLGF has demonstrated a detection rate of 64.0% at 10% false-positive rate for predicting preterm PE [10]. In Korea, the PLGF test is not accepted as a first trimester screening test for predicting PE, despite the availability of the measuring soluble fms-like tyrosine kinase-1/PLGF levels after 20 weeks of gestation. This study showed sensitivities of 54.8% and 66.4% at 10% false-positive rate for predicting PAH and preterm PAH, respectively, by model 2 (a combination of maternal factors and MAP). Furthermore, it should be noted that direct comparisons with the results of other studies regarding the prediction of PE cannot be made [10,34]. In addition, although PAH in this study includes gestational hypertension, which can develop preeclampsia in the almost half of the affected women, there has been no evidence that aspirin can prevent gestational hypertension [35]. This study serves as a preliminary investigation in Korea, encompassing a comprehensive analysis of all available components related to PE.
Although model 2 suggested by this study needs future validation with uterine artery pulsatility index and PAPP-A or without them, our prediction model 2 in a test set and a restricted population showed similar results. The other strength of this study was the BMI classification [36]. The BMI classification into 5 categories for Asian women by the WHO and Korean society for the study of obesity [37,38] provided wide variations in the scores from −3 to 11 points, representing risks from 1.10% to 6.54% in this study.
Although the prevalence of PAH is relatively low in East Asian women, it has been consistently reported that PAH is associated with risks of postpartum hypertension, type 2 diabetes, hyperlipidemia, and cardiovascular diseases across racial and ethnic groups [29,30,39]. In addition, PAH has been suggested to contribute to the development of offspring cardiovascular disease and diabetes later in life [40,41]. Therefore, a prevention strategy for PAH is important not only for decreasing perinatal complications, but also for improving long term health of mothers and their offspring. A recent early prediction model study from Korea using machine learning methods, with clinical factors and blood pressure only, reported an AUC of 0.89 in the training set and 0.81 in the test set, with a sensitivity of 72.7% in the training set and 45.5% in the test set, which showed significantly better performance than a model with PLGF [42]. Although investigating important biomarkers for prediction is important, more studies about the assessment of individual risks of PAH with easily available clinical factors and blood pressure might be more important before introducing several biomarkers.

Conclusions
This preliminary study in Korea developed an early pregnancy risk scoring model for PAH according to basic characteristics of mothers and MAP. A future prospective study for validating this scoring system with biomarkers and uterine artery Doppler (or without them) might be required when discussing the cut-off risk of PAH in East Asian pregnant women.   Figure A1. Participants flow chart of restricted population. PAH, Pregnancy-associated hypertension; PAH_R, Pregnancy-associated hypertension of restricted study population without aspirin treatment.